1. Field of the Invention
The invention relates generally to a method and system for an improved computerized, automatic detection and characterization of lesions in medical images, and more particularly to the detection of circumscribed masses in digital mammograms. Novel techniques in the localization (segmentation) and detection of masses in mammograms, include initially processing with peripheral equalization (correction), a modified median filter, a modified morphological open operation, filtering with a modified mass filter for the initial detection of circumscribed densities, matching using a deformable shape template with Fourier descriptors, optimization of the match using simulated annealing, and measuring the circularity and density characteristics of the suspected lesion to distinguish true positives from false positives and malignant lesions from benign lesions. The procedure is performed iteratively at different spatial resolution in which at each resolution step a specific lesion size is detected. The detection of the mass leads to a localization of a suspicious region and thus the likelihood of cancer.
2. Discussion of the Background
Although mammography is currently the best method for the detection of breast cancer, between 10-30% of women who have breast cancer and undergo mammography have negative mammograms. In approximately two-thirds of these false-negative mammograms, the radiologist failed to detect the cancer that was evident retrospectively. The missed detections may be due to the subtle nature of the radiographic findings (i.e., low conspicuity of the lesion), poor image quality, eye fatigue or oversight by the radiologists. In addition, it has been suggested that double reading (by two radiologists) may increase sensitivity. It is apparent that the efficiency and effectiveness of screening procedures could be increased by using a computer system, as a "second opinion or second reading", to aid the radiologist by indicating locations of suspicious abnormalities in mammograms. In addition, mammography is becoming a high volume x-ray procedure routinely interpreted by radiologists.
If a suspicious region is detected by a radiologist, he or she must then visually extract various radiographic characteristics. Using these features, the radiologist then decides if the abnormality is likely to be malignant or benign, and what course of action should be recommended (i.e., return to screening, return for follow-up or return for biopsy). Many patients are referred for surgical biopsy on the basis of a radiographically detected mass lesion or cluster of microcalcifications. Although general rules for the differentiation between benign and malignant breast lesions exist, considerable misclassification of lesions occurs with current radiographic techniques. On average, only 10-20% of masses referred for surgical breast biopsy are actually malignant. Thus, another aim of computer use is to extract and analyze the characteristics of benign and malignant lesions in an objective manner in order to aid the radiologist by reducing the numbers of false-positive diagnoses of malignancies, thereby decreasing patient morbidity as well as the number of surgical biopsies performed and their associated complications.